Improving DTI resolution from a single clinical acquisition: A statistical approach using spatial prior

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8151 LNCS, Issue PART 3, 2013, Pages 477-484

  Gupta, Vikash ^a   Ayache, Nicholas ^a   Pennec, Xavier ^a  

^a INRIA   (France)

Author keywords

DTI; Partial volume effect; Super resolution

Indexed keywords

ANISOTROPIC REGULARIZATIONS; DTI; MULTIPLE ACQUISITIONS; PARTIAL VOLUME EFFECT; SPATIAL CORRELATIONS; STATISTICAL APPROACH; SUPER RESOLUTION; SUPER RESOLUTION ALGORITHMS;

DIFFUSION TENSOR IMAGING; MAGNETIC RESONANCE IMAGING; MAXIMUM LIKELIHOOD ESTIMATION; MEDICAL COMPUTING; MEDICAL IMAGING; OPTICAL RESOLVING POWER;

TENSORS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; DIFFUSION TENSOR IMAGING; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; MYELINATED NERVE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; ULTRASTRUCTURE;

ALGORITHMS; BRAIN; DATA INTERPRETATION, STATISTICAL; DIFFUSION TENSOR IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84894631870     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40760-4_60     Document Type: Conference Paper

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